Image-to-Text Extraction: Understanding OCR and How It Works

Image-to-Text Extraction: Understanding OCR and How It Works

With the support of OCR technology, text on a page is analysed and converted into code that can be used to process information. When scanning paper records, for example, OCR is a method for identifying printed or handwritten text characters inside digital images of paper files.

Text recognition is another name for optical character recognition (OCR). Data is extracted and reused from scanned documents, camera images, and image-only PDFs by an OCR program.
OCR software allows for the editing of the original content by picking out letters on the image, turning them into words, and then into sentences. Furthermore, it does away with the need for manual data entry.

OCR systems are software and hardware platforms that convert physical documents into text that can be read by computers. In this article, we'll learn about the OCR technology that underlies image-to-text extraction.

What is optical character recognition (OCR) technology?

OCR Technology

Optical character recognition is known as OCR. It is the technology that allows characters to be recognised in an image or physical document and then transformed into editable computerised text.

The method used by the tool or device to extract text from an image will determine whether the algorithm is given specific instructions for each character or uses a database-matching process to identify the characters.

These days, OCR tools can be accessed from desktop computers and mobile devices, respectively, through online tools and apps.

History of optical character recognition (OCR) technology

Ray Kurzweil founded Kurzweil Computer Products, Inc. in 1974. This company's omni-font optical character recognition (OCR) product could read text that was printed in almost any font.

He came to the conclusion that the best use of this technology would be a machine-learning aid for the blind, so he developed a reading machine that could convert text into speech.

In 1980, Kurzweil sold his business to Xerox, which was keen to advance the sale of text conversion from paper to computers. While digitising old newspapers in the early 1990s, OCR technology gained popularity.

How optical character recognition (OCR) work?

Optical character recognition (OCR) uses a scanner to process the picture form of a document. Once all pages are scanned, it converts the image format using a jpg to text converter. The following three are the fundamental core techniques of the programmer:

Image pre-processing

It's crucial to confirm that the accuracy and quality of the scanned documents or image files are up to par before the OCR software can work its magic. Image pre-processing is useful in this situation.

The software, i.e., the tool or application you're using, prepares the image for the character recognition stage during the pre-processing stage. To make it easier to identify the scanned image for the first part, the software gives it a fixed shape and form. When the image is of a real paper or document, this feature comes in particularly handy.

AI character recognition

AI Character Recognition

The next action taken by OCR is to actually recognise the text. To identify characters and numbers, AI examines the dark areas of the image. AI only ever employs one of the following methods at once:

  • Pattern recognition: To train an AI system, technologies use a variety of languages, text types, and handwriting. To find matches, the programme compares the letters on the letter picture it has detected to the notes it has already learned.
  • Feature Recognition: The algorithm recognises new characters by applying rules based on particular character traits. One example of a feature is the quantity of curved, intersecting, or angled lines in a letter.

The software does not compare the characters to a database when performing AI recognition. Instead, it considers the structural elements and personality traits of the characters before converting them.

Post-processing

The final step entails fixing the errors in the data to increase its accuracy. The final result is taught to the AI during the machine learning algorithm's training.

As a result, the programme can compare and check to see if everything conforms to the standard vocabulary and language data, then make the appropriate corrections.

Although English-language documents currently receive the best OCR, other languages are quickly catching up.

The benefits of optical character recognition

The main advantage of optical character recognition (OCR) technology is that it makes text searches, editing, and storage simple, which simplifies data entry.

OCR makes it possible for companies, people, and other entities to store files on their computers, laptops, and other gadgets, guaranteeing ongoing access to all documentation. Other advantages of using an online OCR tool include:

  • Reduce the costs.
  • Accelerate processes
  • Automate document routing and content processing.
  • Saving time and resources
  • Make sure staff members have access to the most recent and accurate information to improve service.
  • Securing data completely


Conclusion

Without a doubt, using intelligent OCR software can change how an organisation manages its document processing. OCR systems will continue to rule the global market as new technologies and abilities like deep machine learning and AI emerge. Researchers predict that as these technologies become more productive and economical, demand for AI-powered OCR will increase.


FAQs (Frequently asked questions)

Is OCR useful for the banking sector?

Yes, along with other industries like insurance and securities, the banking sector is a significant consumer of OCR.

What is Amazon Textract ?

AWS Textract uses AI, machine learning, and OCR to automatically extract text from scanned documents. Textract can also incorporate Amazon Augmented AI to validate sensitive data and carry out human reviews of handwritten documents.